Nowadays most of the fingerprint recognition system operates mainly ontemplate matching basis which requires a lot of memory for data storageand also consumes a lot of time to process the data. It is necessary tobuild a new system which utilizes different techniques in processing thefingerprint that can overcome this problem. This system is called thinning-transformation algorithm.The objective of this project is to develop a system that can extract themain features of the fingerprint pattern and thus identify and classifythe fingerpeint pattern according to the extracted features.In order to gain such objective several techniques are studied in orderto find the most appropriate techniques that be used. The techniques thatare chosen are edge detection, pattern segmentation, interpolation andskeletonization.This project report discusses the techniques that are used and alsothe output obtained after implementing the techniques. Since this projectis new in it's concept, synthetic fingerprint data are used. This is onlyto simplify the calculations. However form the result obtained, the systemcan be further used for real fingerpeint images.During the course of this project all the techniques applied to the inputdata are done manually. This is because the programming part cannot be done in time.